33 results about "Radar equation" patented technology

The invention relates to a radar identification warning method applied to an electric power line protection area, and relates to the technical field of electric power monitoring. According to the method, radar working parameters are configured by using an environment-corrected radar equation and a genetic algorithm considering a radar coverage range, radar detection accuracy and radar energy consumption; the radar detects a target in a power line protection area to obtain radar point cloud data; in the process, multi-frequency fusion ranging is used for measuring the distance of a target, and the Doppler effect is used for resolving the speed of the target; detecting and repairing abnormal values of the radar point cloud data based on an isolated forest algorithm; inputting the preprocessed radar point cloud data into a pre-trained integrated learning classifier for target identification, and obtaining target category information, speed, distance, environment data and facility operation data as risk assessment data; the risk assessment model assesses a target risk according to the risk assessment data to obtain a target risk value and a risk level probability; and performing graded warning according to the target risk value and the risk grade probability.

The invention relates to a fixed-wing unmanned aerial vehicle track anomaly detection method and device and a medium, and the method comprises the steps: building a radar detection noise model based on a radar equation and a signal-to-noise ratio formula; on the basis of the motion equation, simulating the motion process in normal and abnormal states to generate a real track, and adding noise to the real track by using a radar detection noise model to obtain noise-containing simulation track data; constructing a dynamic graph based on the simulated track data; inputting the dynamic graph into a space-time diagram neural network model; the time-space diagram neural network model comprises a diagram attention network layer, a long-short term memory network layer and a linear layer which are connected in sequence; and performing feature extraction and classification on the dynamic graph through a time-space diagram neural network model, and outputting a track anomaly detection result. Therefore, precise detection of tiny track abnormalities of the fixed-wing unmanned aerial vehicle, especially gliding faults and the like, is realized.

The invention discloses a visibility inversion method and device of a laser radar, equipment and a storage medium, and relates to the technical field of laser, and the method comprises the steps: determining a detection range boundary based on a laser radar voltage value and a preset threshold value; synchronously measuring the visibility in a segmented manner by using a ground single-point measurement visibility meter and a laser radar visibility meter, and performing inversion to obtain a function value; constructing a joint relation model by combining a laser radar equation according to the average error of the function value and the radar measurement signal, and generating a parameter mapping relation lookup table; acquiring signal intensity by means of a near-field visibility measuring device, and determining a target laser radar ratio and an extinction coefficient through the look-up table; and finally, resolving an extinction coefficient profile and inverting a visibility profile by adopting a Fernald inversion algorithm in combination with the laser echo signal path, the target extinction coefficient and the laser radar ratio. The efficiency of laser radar visibility inversion is improved.

The invention relates to a direct assimilation method and system for an aerosol attenuation backscattering coefficient, and relates to the technical field of data assimilation of atmospheric aerosol. The method comprises the following steps: based on a laser radar equation, constructing a nonlinear observation operator of a direct assimilation aerosol attenuation backscattering coefficient by adopting a Mie scattering theory; according to a three-dimensional variational assimilation theory and a nonlinear observation operator, constructing an assimilation model for solving an aerosol attenuation backscattering coefficient of an objective function minimum solution; acquiring assimilated laser radar aerosol observation data for preprocessing, and inputting the preprocessed observation data into an assimilation model; and operating the assimilation model, taking the minimum solution obtained by solving as an aerosol increment field, and superposing the aerosol increment field to a background field to obtain an analysis field of the aerosol. According to the method, direct assimilation of the first-level observation data of the laser radar aerosol is realized, more accurate aerosol initial distribution is provided for the mode after assimilation, and a more accurate aerosol analysis and prediction result can be obtained.

A coherent wind lidar echo signal spectrum simulation data generation method is provided, comprising: obtaining the bottom noise of the echo signal; removing the bottom noise from the echo signal spectrum data and counting the variance of the random noise; performing normalization processing on the random noise and performing Gaussian fitting to obtain the amplitude, Doppler shift and bandwidth of the echo signal; recording the Doppler shift difference between adjacent range gates to obtain the power spectrum peak energy of a single spectrum data and the correction amount of the distance; respectively counting the statistical parameters of the random variable, the power spectrum peak energy, the correction amount of the distance and the bandwidth; generating a group of wind speed profile graphs by using random walk and normal distribution characteristics of random variables, generating bandwidths under different range gates that satisfy the Lorentz distribution, power spectrum peak energies of a single simulated spectrum that satisfy the chi-square distribution, and distance correction amounts that satisfy the normal distribution; and generating a single simulated spectrum by a radar equation and repeatedly generating complete spectrum simulation data.

The present invention proposes a performance evaluation method for a long-distance space reflection communication system. The reflection communication system includes a transmitter, a receiver, and a reflector. The transmitter is configured to emit a transmission signal, the reflector is configured to reflect the transmission signal to obtain a reflection signal, and the receiver is configured to receive the reflection signal. The method comprises obtaining device parameters of the reflection communication system and position information of the transmitter, receiver, and reflector; calculating a basic reflection communication link budget for the reflection communication system based on a bistatic radar equation; calculating a beam pattern based on the device parameters, and calculating a correction coefficient based on the beam pattern and position information; and using the correction coefficient to correct the basic reflection communication link budget to obtain a corrected reflection communication link budget value, thereby achieving link performance evaluation.

The invention relates to the technical field of radar signal processing and radar imaging, in particular to a millimeter wave MIMO-SAR imaging method based on beam forming optimization, and the method comprises the steps: configuring an MIMO radar array; according to the radar equation and the point target model, simulating an actual echo data matrix of a preset focus in the imaging area; constructing a beam forming optimization model according to the MIMO radar array; solving the beam forming optimization model through an optimization algorithm to obtain an optimal weight vector; weighting and summing the optimal weight vector and the actual echo data matrix to obtain a composite signal; and performing imaging processing on the synthetic signal to generate an SAR image. According to the method, the imaging quality and the target resolution capability in a low signal-to-noise ratio environment are improved by constructing the beam forming optimization model and solving the optimal weight vector; meanwhile, the signal focusing effect is enhanced by optimizing weighted synthesis, and the resource utilization efficiency of the system in a key area is remarkably improved while high-resolution radar imaging is achieved.

The application discloses a multi-radar power envelope fusion method, comprising: single-radar envelope modeling, constructing envelope fusion foundation; determining non-coherent field fusion, constructing multi-radar envelope model; constructing gradient diffusion model, realizing envelope fusion smooth transition; displaying Euler method iteration convergence, realizing multi-radar envelope complete fusion; adopting adaptive octree structure to dynamically divide three-dimensional space. Advantageous effects: the multi-radar power envelope fusion method firstly calculates single-station detection probability of each radar unit at a grid point in a three-dimensional space voxel according to a radar equation, a propagation loss model and target scattering characteristics; then adopts a probability union or a more complex dependent relationship model to generate a full-space joint detection probability field; finally, an isosurface extraction (such as an improved Marching Cubes algorithm) and a probability gradient driven color / transparency mapping are adopted to generate a visual continuous, mathematically accurate fusion envelope surface.

The application discloses a snow depth inversion method and system based on underlying surface information fusion of a SAR image, relates to the technical field of ice and snow monitoring based on satellite remote sensing technology, and comprises the following steps: collecting orbit data, pre-processing the collected orbit data, removing thermal noise and speckle noise, performing terrain correction, and obtaining a backscattering characteristic parameter and a polarization characteristic parameter according to a radar equation for radiation calibration, performing feature extraction on the corrected data, optimizing a feature data set, constructing a neural network model, inputting the optimized feature data set into a residual neural network, training to obtain a snow depth inversion model, and introducing a time variable to predict the snow depth. The application effectively solves the problems of snow depth inversion and prediction by fusing advanced SAR data processing technology and a machine learning method, and provides an important basis for decision support.

The invention belongs to the technical field of false alarm suppression, and particularly relates to a backward lobe clutter false alarm suppression method for an airborne PD radar, and the method comprises the steps: carrying out the RCS modeling based on the preprocessed single-point measurement data through a radar equation and system parameters; rCS filtering is carried out on the preprocessed single-point measurement data through RCS modeling; the method comprises the following steps: establishing a track for single-point measurement meeting an RCS threshold, scheduling the track to obtain scheduling frame measurement, setting a sliding window to smooth the scheduling frame measurement to obtain a track RCS, judging a filtering threshold of the track RCS, deleting the track which does not meet the filtering threshold, and obtaining a track of a real target. Compared with a method of adding a wave-absorbing material, the method does not add additional hardware, does not increase the weight of a product, and does not have additional cost; and the element dimension of the target calculation information is increased, and the reliability of measuring a single point is improved. The flight path level situation and the RCS physical characteristics are jointly judged, the reliability of real flight path association is improved, and the duration of a false alarm flight path is restrained.

This invention discloses a method for simulating and modeling chaff cloud echoes, comprising: calculating the full-space single-base scattering characteristics of individual chaff strips of different lengths using the Pocklington integral equation; generating the scattering characteristics of each chaff strip using Lagrange interpolation based on a randomly generated or existing chaff cloud model; obtaining the echo of each chaff strip according to the relative position between the detector and the chaff strip, combined with radar equations, and vector-superimposing the echo contributions of all chaff strips to form the overall echo of the chaff cloud; and calculating the echo characteristic curve of each sampling point on the detector's motion trajectory one by one according to the above steps. This invention considers the scattering of chaff strips from the perspective of the scattering center, enabling efficient simulation of chaff cloud echo characteristics, and meeting current engineering requirements in terms of both accuracy and speed.

The invention discloses a multi-radar power envelope fusion method, which comprises the steps of performing single-radar envelope modeling, and constructing an envelope fusion foundation; incoherent field fusion is determined, and a multi-radar envelope model is constructed; constructing a gradient diffusion model to realize envelope fusion smooth transition; euler method iterative convergence is displayed, and multi-radar envelope complete fusion is realized; and dynamically dividing a three-dimensional space by adopting a self-adaptive octree structure. The multi-radar power envelope fusion method has the beneficial effects that firstly, according to a radar equation, a propagation loss model and target scattering characteristics, the single-station detection probability of each radar unit at a grid point is calculated in a three-dimensional space voxelization mode; a probability union set or a more complex dependency relationship model is adopted, and a total-space joint detection probability field is generated through fusion; finally, through contour surface extraction (such as an improved March i ng Cubes algorithm) and color / transparency mapping driven by probability gradient, a fusion envelope curved surface with continuous vision and accurate mathematics is generated.

The present invention provides a method for optimizing the configuration of a collaborative detection formation with a networked airborne radar and a split transmitter-receiver configuration, relating to the technical field of multi-aircraft collaborative detection. The method first initializes the combat environment between the enemy and friendly forces and sets evaluation indicators for friendly forces' detection effectiveness. A radar equation for a system with split transmitters and receivers is then established to calculate the detection power of friendly forces' radars against enemy aircraft. A mathematical model is then established to evaluate the optimization effect of the split transmitter-receiver collaborative detection formation configuration. Finally, an improved artificial fish school algorithm is proposed to search for the optimal configuration of the split transmitter-receiver collaborative detection formation. The proposed method for optimizing the configuration of a networked airborne radar and a split transmitter-receiver collaborative detection formation not only improves the survivability of the transmitter but also satisfies the receiver's need for covert target detection.

The application discloses a kind of antenna directional pattern measurement methods based on segmented gain variable threshold single-bit receiver, it is related to synthetic aperture radar radiometric calibration technical field.The method steps are as follows: the monotonic relationship of quantitative signal power and STR is analyzed, and quantitative model is established;The receiving signal amplitude reconstruction strategy of all sampling rate and SAR bandwidth ratio is constructed;The maximum amplitude and minimum amplitude of received signal are determined, the received signal amplitude is segmented and threshold is set;Signal spectrum is analyzed and quantitative signal power is estimated;STR and actual received signal power are calculated;Azimuth and range antenna directional pattern sample value are calculated, and according to radar equation, radar antenna azimuth and pitch gain is calculated, and antenna directional pattern is reconstructed using polynomial fitting.The application simplifies the structure of radar directional pattern gain measurement receiver, reduces the cost, guarantees the measurement accuracy, and can meet the demand of large-scale deployment and high-precision estimation of SAR radiometric calibration active receiver.

The invention relates to the technical field of wireless communication, in particular to an FPGA-based Rice channel simulation method, system and chip, and the method comprises the steps: generating a time slice according to the maximum Doppler frequency shift; initializing Doppler frequency shift parameters of each scattering path; in each time slice, generating a direct path complex envelope and synchronously generating a plurality of scattering path complex envelopes according to the current parameters; updating Doppler frequency shift parameters of the scattering path at the end of each time slice; calculating an amplitude coefficient based on a Rice factor and the simulated propagation delay of each scattering path, and carrying out amplitude modulation; and synthesizing and outputting all path complex envelopes. According to the method, the real-time calculation burden of the FPGA is reduced through a time slicing mechanism, and power distribution is performed based on a radar equation, so that a simulation result better conforms to real channel characteristics.

The invention discloses a diffraction theory-based method for evaluating the influence of an offshore wind farm on radar detection, and particularly relates to the technical field of offshore wind farms, comprising the following steps: S1, scene modeling and parameter collection, S2, fan shield modeling, and S3, result output and influence evaluation. According to the method for evaluating the influence of the offshore wind power plant on radar detection based on the diffraction theory, a parameter collection-modeling-evaluation full-process system is constructed, radar and wind power plant parameters are comprehensively collected, grid division is carried out on a detection area, weights are assigned according to the target occurrence frequency, and the target occurrence frequency is calculated; and then outputting a diffraction loss and field intensity decline distribution diagram, and finally quantitatively calculating a detection distance shortening proportion, a detection probability decline degree and an overall influence degree through weighted averaging in combination with a radar equation and a detection model, thereby providing a clear quantitative engineering decision basis for a wind power plant to plan and avoid a radar key path and optimizing a radar system.

This invention discloses a gridded visualization method for scanning lidar detection data, belonging to the field of lidar detection and geographic information system visualization technology. The method comprises the following steps: S1: Constructing a three-dimensional grid spatial model; S2: Collecting raw detection data from the scanning lidar, performing spatiotemporal synchronization and coordinate transformation, and mapping each detection point to the corresponding grid cell of the three-dimensional grid spatial model; S3: For each grid cell, statistically analyzing the historical detection hit count and theoretical scan count, and combining the lidar equation and atmospheric extinction model to calculate at least one detection capability index; S4: Generating visualization rendering data with optimized color mapping, transparency, and hierarchical details based on the detection capability index; S5: Rendering the visualization rendering data using a three-dimensional graphics engine and providing interactive analysis functions to achieve gridded visualization of detection capabilities. This invention improves the accuracy, intuitiveness, and interactive efficiency of lidar detection performance evaluation.

The application belongs to but is not limited to the technical field of radar signal processing, and discloses a networking radar interception probability performance evaluation method and system, a networking radar system model is established, the networking radar system comprises a plurality of transmitting nodes; radiation power is calculated: the radiation power of each transmitting node at each position in space is calculated through a radar equation; a critical signal-to-noise ratio of an interception receiver is calculated: the critical signal-to-noise ratio of a signal intercepted by an interceptor is obtained according to the detection probability and the false alarm probability of the interceptor; the equivalent radius of an easy interception area is calculated: according to the radiation power and the critical signal-to-noise ratio, the easy interception area of the networking radar is obtained, and then the corresponding equivalent radius of the easy interception area is calculated. The low-interception performance evaluation index of the application has clear physical meaning, can be used as a target function or a constraint condition to optimize radar parameters in the design of a low-interception probability radar, and reduces the probability that the radar system is intercepted.

The invention relates to the technical field of meteorological radar detection and data processing, and discloses a multi-mode collaborative compact X-waveband weather radar system, which comprises a plurality of radar nodes, and adopts a time division collaborative mechanism to divide a work period into active detection and passive collaborative time slots. The node integrates a main observation and omnidirectional cooperative antenna, and the cooperative sequential control unit is switched between a precise calibration mode and a background maintenance mode according to beam pointing. And the baseband signal processing subsystem executes a self-adaptive frequency spectrum avoidance strategy, and enables the reference signal to avoid a meteorological echo main energy region by injecting the optimal frequency offset. The system utilizes a radar equation reverse solution logic to decouple and separate system gain drift and radome water film attenuation from a received signal, and performs networking data fusion in combination with a calibration confidence coefficient weight. On the premise that meteorological services are not interrupted, online mutual calibration and physical parameter decoupling of the whole network are achieved, and the observation consistency of the X-band radar network under the complex weather condition is remarkably improved.

The present invention belongs to the field of electromagnetic information, and provides a method for calculating the radar detection power range for accompanying support jamming. The method includes: (10) performing data collection to obtain the basic radar parameters. (20) calculating the maximum detection range of the base radar. (30) determining whether there is an aircraft penetration. If there is no aircraft penetration, directly render through the Cesium tool according to the calculated maximum detection range to display the visualization effect without interference. Otherwise, plan the route of the penetrating aircraft. (40) determining the number of accompanying support jamming forces. (50) calculating the radar detection power range under accompanying support jamming. Render through the Cesium tool to achieve dynamic three-dimensional visualization. The beneficial effects are as follows: combining the visualization system with the interference suppression model to form an accompanying adaptive support interference suppression area model. First, establish a mathematical model based on the radar pattern function and detection distance as parameters through the basic radar equation, and then combine the implementation algorithm of the maximum radar detection range, and use the Cesium visualization tool to render the radar interference exposure area. This method can be used to accurately implement interference and penetration strategies, scientifically plan the assault and escort routes, and verify the effectiveness and rationality of the model system.

The invention provides a millimeter wave radar RCS data feature analysis system and method based on a space-time diagram neural network, and the system comprises a data preprocessing and construction module which carries out the preprocessing of RCS data and construction of a space-time diagram through obtaining RCS time series data collected by a plurality of types of millimeter wave radars; the time-space diagram neural network modeling module is used for extracting spatial features through GCNs (Graph Convolution Neural Neural Network) and capturing time sequence changes through TCN (Time Convolution Neural Neural Network); the cross-modal feature decoupling module is used for separating target attributes, environmental noise and radar parameter difference values through a physical constraint loss function; and the GAN small sample data enhancement module is used for generating virtual RCS data conforming to a radar equation and expanding a low-frequency target data set.

The invention belongs to the technical field of radar detection, and particularly relates to a dual-radar cooperative transmit-receive split simulation implementation method, which comprises the following steps of: 1, creating simulation radar models of a receiver, a transmitter and a target; 2, setting radar parameter values of a receiver and a transmitter in a radar equation; step 3, taking a dual-machine RCS value sigma B called from a database, a distance RT between a transmitter and a target, a distance RR between a receiver and the target, and a distance RL between the transmitter and the receiver as inputs, substituting the inputs into the radar equation for calculation, and obtaining a minimum detectable signal-to-noise ratio D; and 4, when the minimum detectable signal-to-noise ratio D is greater than a set threshold value, determining that the target is detectable, and otherwise, determining that the target is not detectable.

The application provides a laser radar networking monitoring method based on intelligent cooperation and closed-loop optimization, and relates to the technical field of data processing.The method comprises the following steps: constructing a deep neural network, taking a laser radar equation as a physical constraint, combining consistency of multiple radar overlapping areas, inverting extinction and backscattering coefficients and quantifying confidence; using uncertainty dynamic optimization scanning parameters to encrypt scanning in a high-uncertainty area and pre-scanning a high-information-gain area; embedding self-supervised calibration into inversion loss, based on physical residual to reverse repair abnormal points; fusing inversion, calibration and uncertainty confidence to construct an adaptive interpolation kernel and a space-time physical constraint, and reconstructing a four-dimensional data field; and fusing comprehensive confidence to map to transparency to construct an interactive four-dimensional visualization platform.The application realizes closed-loop self-optimization of inversion, calibration, scanning, interpolation, visualization and tracing, improves inversion precision and data reliability, and reduces operation and maintenance cost and energy consumption.

The invention discloses a method and device for measuring a complex scattering function of a radar target, and relates to the field of microwave stealth technology and active microwave remote sensing, and the method comprises the steps: constructing a generalized radar equation represented by a complex voltage for a radar detection target; according to the generalized radar equation, fitting to obtain a relation curve of the amplitude and the distance of the complex scattering function and a relation curve of the phase and the distance; performing low-pass filtering processing on the relation curve of the amplitude and the distance and the relation curve of the phase and the distance; and for the relation curve of the amplitude and the distance after filtering and the relation curve of the phase and the distance after filtering, obtaining the amplitude and the phase of the complex scattering function at the infinite far field by adopting a polynomial fitting and limit taking method. According to the invention, the method can directly and accurately measure the complex scattering function of any small to-be-measured target (including a standard device), and does not need an RCS standard device with a known standard value in the measurement process.

The invention specifically discloses an antenna pattern measurement method based on a segmented gain variable threshold single-bit receiver, and relates to the technical field of synthetic aperture radar radiometric calibration. The method comprises the following steps: analyzing a monotonic relationship between quantized signal power and STR, and establishing a quantitative model; constructing a received signal amplitude reconstruction strategy of all sampling rates and SAR bandwidth ratios; determining the maximum amplitude and the minimum amplitude of the received signal, segmenting the amplitude of the received signal, and setting a threshold value; analyzing the signal spectrum and estimating quantized signal power; calculating the STR and the actual received signal power; and calculating azimuth and distance antenna pattern sampling values, calculating azimuth dimension and pitching dimension gains of the radar antenna according to a radar equation, and reconstructing an antenna pattern by using polynomial fitting. According to the invention, the structure of a radar pattern gain measurement receiver is simplified, the cost is reduced, the measurement precision is guaranteed, and the large-scale deployment and high-precision estimation requirements of an SAR radiometric calibration active receiver can be met.

This invention discloses a radar countermeasure effectiveness evaluation method based on MBSE model construction. This method uses a model-based systems engineering approach, starting from the detection principle of radar countermeasures, to characterize and design the model construction. The model design studies radar equations, interference signal modulation methods, interference effects, and other aspects, analyzes user and functional requirements of the model, and uses these requirements to drive the design. The overall composition and performance of the coordinated model are optimized to ensure consistency among requirements, functions, and models. This invention utilizes an MBSE-based model construction method to unify and collaboratively design countermeasure models. Under existing circumstances, it can effectively implement the design and simulation of radar countermeasure models and the evaluation of countermeasure effectiveness.

The present invention discloses a method for designing laser radar hardware parameters based on a laser radar equation simulation model, and belongs to the field of laser radar remote sensing detection technology. Based on the laser radar equation simulation model, the present invention can analyze the influence of laser radar parameters such as different laser wavelengths, energies, pulse widths, divergence angles, field angles, repetition frequencies, telescope apertures, laser inclination angles in the visible light band, as well as water body bio-optical parameters and environmental parameters such as chlorophyll concentration, absorption coefficient, scattering coefficient, scattering phase function, wind speed, zenith angle, etc. on multi-platform laser radar receiving signals; finally, by changing different parameters, the laser radar receiving signal strength is analyzed and the system parameter design is optimized. The present invention has fast operation speed and high calculation efficiency, and the input parameters can be conveniently adjusted according to the laser radar system and environment; it can be used to simulate the signals of multi-platform ocean laser radars such as shipborne, airborne and satellite-borne.

The invention discloses a meteorological remote sensing radar SCR simulation method. The method comprises the steps that a Taylor window function is used for constructing a three-dimensional antenna directional diagram under a required side lobe; constructing a clutter power model in a surface area unit based on remote sensing radar observation geometry; based on a clutter power model in a surface area unit, establishing a mapping relation between the surface and a three-dimensional antenna pattern, and calculating the total surface clutter power; calculating the total echo power of the meteorological target based on the meteorological radar equation; and combining the total clutter power of the earth surface with the echo power of the meteorological target to obtain an SCR distribution curve. The method is suitable for SCR modeling and simulation of satellite-borne, airborne, boat-borne and other remote sensing platform observation scenes, and a theoretical basis and simulation support are provided for performance evaluation, antenna parameter design and clutter suppression strategies of a meteorological remote sensing radar system.

A method and system for arranging sparse array antennas for ultra-wideband (UWB) positioning are disclosed, relating to the field of UWB signal modulation. This invention addresses the problem that hardware limitations in the transmission and reception of UWB signals significantly reduce the effective range and accuracy of UWB signal location estimation, resulting in a large discrepancy between practical application and theoretical limits. The method includes: matching antenna elements according to the desired UWB signal; solving for the main lobe gain of the array antenna based on the desired maximum radar range and radar equations; optimizing the main lobe gain and sidelobes of the array antenna using a genetic algorithm to obtain the array's positional distribution; and arranging the array sparsely according to the positional distribution. This invention is applied to the field of radar ranging.